Collaborative Research: Design of Dense RFID Systems for Indexing in the Physical World Across Space, Time, and Human Experience

合作研究：设计用于跨空间、时间和人类经验的物理世界索引的密集 RFID 系统

• 批准号: 0725864
• 负责人: Vikram Jandhyala
• 金额: $ 12.6万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-15 至 2010-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0725864&HistoricalAwards=false
• 关键词: Collaborative; Research; Design; Dense; RFID

Integrative, Hybrid and Complex SystemsHari Sundaram, Arizona State UniversityVikram Jandhyala, University of WashingtonCollabortive Research: Design of Dense RFID Systems for Indexing in the Physical World across Space, Time, and Human ExperienceIntellectual Merit: Radio frequency identification (RFID) technology embeds small, inexpensive, and passively-powered radio tags in physical objects. Many potential innovative applications of RFID are not yet supported by current technology. This research pursues a multidisciplinary, integrative approach to investigate fundamental technical challenges in RFID, both at the physical and data management layers, to realize innovative data-centric applications such as attribute-based object search. The research focuses on two areas, distributed data management, and (ii) physical layer limitations. The research will investigate data structures that can resolve queries for remote objects by only accessing local tags within a specified radio range; efficient encoding of symbolic and numeric logical attributes to address the cost of associative search and random access to a large data structure from a single tag; and redundancy-based algorithms for overcoming data access reliability limitations and access failures in dense tag environments. At the physical layer, the research will address issues due to tag density, the need for extended memory storage, and the absence of on-chip power.Broader Impact: This research has the potential to aid individuals in living in increasingly complex environments. The research will aid in the development of new course modules on large-scale dense RFID simulation at the University of Washington and robust information dissemination at Arizona State University. The project will also allow students at both universities to experiment with various aspects of RFID-based distributed information management, thus increasing student awareness of mechanisms for addressing information-overload and privacy issues that arise due to increasingly widespread, yet loosely controlled, digital "footprints."

综合、混合和复杂系统Hari Sundaram，亚利桑那州立大学Vikram Jandhyala，华盛顿大学合作研究：设计用于在物理世界中跨空间、时间和人类体验进行索引的密集 RFID 系统智力优点：射频识别 (RFID) 技术将小型、廉价且无源供电的无线电标签嵌入到物理对象中。 当前技术尚不支持 RFID 的许多潜在创新应用。 这项研究采用多学科、综合的方法来研究 RFID 在物理层和数据管理层的基本技术挑战，以实现以数据为中心的创新应用，例如基于属性的对象搜索。 该研究重点关注两个领域：分布式数据管理和 (ii) 物理层限制。 该研究将研究能够通过仅访问指定无线电范围内的本地标签来解决远程对象查询的数据结构；符号和数字逻辑属性的有效编码，以解决关联搜索和从单个标签随机访问大型数据结构的成本；基于冗余的算法，用于克服密集标签环境中的数据访问可靠性限制和访问失败。 在物理层，该研究将解决由于标签密度、扩展内存存储的需要以及片上电源缺乏而导致的问题。更广泛的影响：这项研究有可能帮助个人生活在日益复杂的环境中。 该研究将有助于华盛顿大学大规模密集 RFID 模拟和亚利桑那州立大学强大信息传播的新课程模块的开发。 该项目还将允许两所大学的学生尝试基于 RFID 的分布式信息管理的各个方面，从而提高学生对解决由于日益广泛但松散控制的数字“足迹”而出现的信息过载和隐私问题的机制的认识。